Identification and classification of evaluation indicators for scientific and technical publications and related factors by Hassan Mahmoudi Topkanlo, Mehrdad CheshmehSohrabi

“…Given the importance of the issue of the widespread impact of scientific and technical publications in today's world, and the diversity and multiplicity of indicators for measuring these publications, it is a necessity to classify these indicators from different angles and through different tools and methods. …”
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Research on Pedestrian and Cyclist Classification Method Based on Micro-Doppler Effect by Xinyu Chen, Xiao Luo, Zeyu Xie, Defang Zhao, Zhen Zheng, Xiaodong Sun

“…However, due to the strong temporal similarity between pedestrians and cyclists, the insensitivity of the traditional least squares method to their differences results in its suboptimal classification performance. In response to this issue, this paper proposes an algorithm for classifying pedestrian and cyclist targets based on the micro-Doppler effect. …”
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Intelligent Classification of Stable and Unstable Slope Conditions Based on Landslide Movement by Long Tsang, Ali Ghorbani, Seyed Mohammad Hossein Khatami, Dmitrii Ulrikh

“…Three models of Tree, Adaboost and artificial neural network (ANN) were developed for classification into two categories, stable and unstable. …”
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Dialect Classification and Everyday Culture: A Case Study from Austria by Philip C. Vergeiner

“…This study addresses this issue by employing a multivariate, dialectometric approach. …”
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Classification performance improvement in imbalanced circumferential guided wave detection data by Yu-hang Zhang, Xu Zhang, Yuan-hang Gu, Li-min Fu, Xin-ran Su, Jun-dong Yuan, Qiao Wu

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A comprehensive evaluation of oversampling techniques for enhancing text classification performance by Salimkan Fatma Taskiran, Bahaeddin Turkoglu, Ersin Kaya, Tunc Asuroglu

“…According to the “garbage in, garbage out” principle, even high-performing models may fail when trained on skewed distributions. To address this issue, this study investigates the impact of oversampling techniques, specifically the Synthetic Minority Over-sampling Technique (SMOTE) and thirty of its variants, on two benchmark text classification datasets: TREC and Emotions. …”
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Addressing imbalanced data classification with Cluster-Based Reduced Noise SMOTE. by Javad Hemmatian, Rassoul Hajizadeh, Fakhroddin Nazari

“…In recent years, the challenge of imbalanced data has become increasingly prominent in machine learning, affecting the performance of classification algorithms. This study proposes a novel data-level oversampling method called Cluster-Based Reduced Noise SMOTE (CRN-SMOTE) to address this issue. …”
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THE TOPONYMY OF THE VILLAGE OF PADESH, BLAGOEVGRAD AREA – SEMANTIC CLASSIFICATION AND STRUCTURAL SPECIFICS by Nadelina Ivova

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Learning From Natural Images in Few-Shot SAR Target Classification by Songhao Shi, Xiaodan Wang, Yafei Song

“…The intricate imaging attributes of synthetic aperture radar (SAR) present a formidable challenge to the prevailing few-shot target classification. In order to address this issue, we study how to leverage natural images to assist with few-shot SAR learning and propose a model with cross-domain generalization ability, named CDFS-SAR. …”
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Odor classification: Exploring feature performance and imbalanced data learning techniques. by Durgesh Ameta, Surendra Kumar, Rishav Mishra, Laxmidhar Behera, Aniruddha Chakraborty, Tushar Sandhan

“…We evaluated their performance using four different multi-label classification models. The second objective is to address an inherent challenge in odor classification multi-label datasets (MLD)-the issue of class imbalance by random resampling techniques and an explainable, cost-sensitive multilayer perceptron model (CSMLP). …”
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Harmonization for Parkinson’s Disease Multi-Dataset T1 MRI Morphometry Classification by Mohammed Saqib, Silvina G. Horovitz

“…We conclude that batch effects remain a major issue for classification problems, such that even impressive single-scanner classifiers are unlikely to generalize to multiple scanners, and that solving for batch effects in a classifier problem must avoid circularity and reporting overly optimistic results.…”
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An enhanced text classification model by the inverted attention orthogonal projection module by Hong Zhao, Chenpeng Zhang, Aolong Wang

“…The orthogonal projection method has made significant progress in text classification, especially in generating discriminative features. …”
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Crime Prediction Using Decision Tree (J48) Classification Algorithm. by Ivan, Niyonzima, Emmanuel Ahishakiye, Elisha Opiyo Omulo, Danison Taremwa

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Real-time classification of EEG signals using Machine Learning deployment by Swati CHOWDHURI, Satadip SAHA, Samadrita KARMAKAR, Ankur CHANDA

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Plant disease classification in the wild using vision transformers and mixture of experts by Zafar Salman, Abdullah Muhammad, Dongil Han

“…Plant disease classification using deep learning techniques has shown promising results, especially when models are trained on high-quality images. …”
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Evaluation of the practical application of the category-imbalanced myeloid cell classification model. by Zhigang Hu, Aoru Ge, Xinzheng Wang, Cuisi Ou, Shen Wang, Junwen Wang

“…Therefore, developing a reliable automated model for myeloid cell classification is imperative. This study evaluated the performance of five widely-used classification models on the largest publicly available bone marrow cell dataset (BM). …”
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A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification by Lilu Wang, Yongqi Li, Haiyuan Liu, Taihui Liu

“…This limitation hinders their deployment on resource-constrained edge devices. To address this issue, we propose TBiGNet, a lightweight Transformer-based classification network model for RUL prediction. …”
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Mastitis Classification in Dairy Cows Using Weakly Supervised Representation Learning by Soo-Hyun Cho, Mingyung Lee, Wang-Hee Lee, Seongwon Seo, Dae-Hyun Lee

“…Therefore, this study proposed a mastitis classification based on weakly supervised representation learning using an autoencoder on time series milking data, which allows for concurrent milking representation learning and weakly supervision with low-cost labels. …”
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Information Merging for Improving Automatic Classification of Electrical Impedance Mammography Images by Jazmin Alvarado-Godinez, Hayde Peregrina-Barreto, Delia Irazú Hernández-Farías, Blanca Murillo-Ortiz

“…However, analyzing these layers individually can be redundant and complex, making it difficult to identify relevant features for lesion classification. To address this issue, advanced computational techniques are employed for image integration, such as the Root Mean Square (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>C</mi><mi>RMS</mi></msub></semantics></math></inline-formula>) Contrast and Contrast-Limited Adaptive Histogram Equalization (CLAHE), combined with the Coefficient of Variation (CV), CLAHE-based fusion, weighted average fusion, Gaussian pyramid fusion, and Wavelet–PCA fusion. …”
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RGB Color Space-Enhanced Training Data Generation for Cucumber Classification by Hotaka Hoshino, Takuya Shindo, Takefumi Hiraguri, Nobuhiko Itoh

“…To address this issue, this study aims to develop a classification system that enables individuals, regardless of their level of expertise, to accurately classify cucumbers. …”
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